Integration and Analysis of Omics Data Using Genome-Scale Metabolic Models

Dear Colleagues,

Genome-scale metabolic models (GEMs) have been vastly employed in different fields of science, ranging from bioengineering and synthetic biology to systems biology and medicine. A relatively wide scope of GEM applications includes the computational analysis of omics data, which complements existing bioinformatics pipelines. In this context, GEMs can not only be used to analyze experimental data, but also to generate and test novel hypotheses using in silico experimentation mainly derived from constraint-based approaches. However, the biological significance of the results of so-called context-specific models (i.e., models adapted to specific data describing a given context) depends on different factors. These include (1) the quality of the reference GEM used as a scaffold for the reconstruction, (2) the selection of a model extraction method (MEM) used in the process of the reconstruction, and (3) the configuration of a MEM and environmental constraints used for the reconstruction. Several challenges that would increase the reproducibility of obtained GEMs as well as the quality of the obtained results should be addressed. Important aims of the constraint-based modelling community also include the proposal of computational pipelines and protocols that would allow for a straightforward reconstruction and analysis of high-quality context-specific GEMs. Additionally, the experimental validation of hypotheses generated in silico using GEMs is needed. This Special Issue is devoted to original scientific papers as well as reviews describing recent efforts in the context of the reconstruction of context-specific GEMs, their validation, and analysis.

Dr. Miha Moškon
Dr. Tadeja Režen
Guest Editors

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